In a manufacturing process, manufacturing data is quite a lot and is difficult to be analyzed. For improving the manufacturing process, a big data technology, such as model diagnosis, may be used to analyze the manufacturing data. For example, in the semiconductor process, the root cause of yield loss may be more than one and needed to be picked out adequate and statistical meaning models to find out key factors.
However, the number of the models is too huge, so it is needed to invent a useful method and system to screen and reserve top few key models, such that the key models and the key factors thereof can be efficiently found.